Diagnostics,
Год журнала:
2022,
Номер
12(9), С. 2110 - 2110
Опубликована: Авг. 31, 2022
The
increasing
usage
of
smart
wearable
devices
has
made
an
impact
not
only
on
the
lifestyle
users,
but
also
biological
research
and
personalized
healthcare
services.
These
devices,
which
carry
different
types
sensors,
have
emerged
as
digital
diagnostic
tools.
Data
from
such
enabled
prediction
detection
various
physiological
well
psychological
conditions
diseases.
In
this
review,
we
focused
applications
wrist-worn
wearables
to
detect
multiple
diseases
cardiovascular
diseases,
neurological
disorders,
fatty
liver
metabolic
including
diabetes,
sleep
quality,
illnesses.
fruitful
requires
fast
insightful
data
analysis,
is
feasible
through
machine
learning.
discussed
machine-learning
outcomes
for
analyses.
Finally,
current
challenges
with
data,
future
perspectives
tools
domains.
PLOS Digital Health,
Год журнала:
2022,
Номер
1(10), С. e0000104 - e0000104
Опубликована: Окт. 13, 2022
Wearable
devices
are
increasingly
present
in
the
health
context,
as
tools
for
biomedical
research
and
clinical
care.
In
this
wearables
considered
key
a
more
digital,
personalised,
preventive
medicine.
At
same
time,
have
also
been
associated
with
issues
risks,
such
those
connected
to
privacy
data
sharing.
Yet,
discussions
literature
mostly
focused
on
either
technical
or
ethical
considerations,
framing
these
largely
separate
areas
of
discussion,
contribution
collection,
development,
application
knowledge
has
only
partially
discussed.
To
fill
gaps,
article
we
provide
an
epistemic
(knowledge-related)
overview
main
functions
wearable
technology
health:
monitoring,
screening,
detection,
prediction.
On
basis,
identify
4
concern
functions:
quality,
balanced
estimations,
equity,
fairness.
move
field
forward
effective
beneficial
direction,
recommendations
areas:
local
standards
interoperability,
access,
representativity.
Journal of Medical Internet Research,
Год журнала:
2022,
Номер
24(7), С. e36690 - e36690
Опубликована: Май 16, 2022
Chronic
diseases
contribute
to
high
rates
of
disability
and
mortality.
Patient
engagement
in
chronic
disease
self-management
is
an
essential
component
models
health
care.
Wearables
provide
patient-centered
data
real
time,
which
can
help
inform
decision-making.
Despite
the
perceived
benefits
wearables
improving
self-management,
their
influence
on
care
outcomes
remains
poorly
understood.This
review
aimed
examine
individuals
with
through
a
systematic
literature.A
narrative
was
conducted
by
searching
6
databases
for
randomized
observational
studies
published
between
January
1,
2016,
July
2021,
that
included
use
wearable
intervention
group
assess
its
impact
predefined
outcome
measure.
These
were
defined
as
any
patient
or
clinician
experience,
cost-effectiveness,
result
intervention.
Data
from
extracted
based
key
themes,
formed
basis
qualitative
synthesis.
All
mapped
against
each
Quadruple
Aim
The
guidelines
PRISMA
(Preferred
Reporting
Items
Systematic
Reviews
Meta-Analyses)
statement
followed
this
study.A
total
30
articles
included;
reported
2446
participants
(mean
age:
range
10.1-74.4
years),
14
types
18
presented.
most
studied
type
2
diabetes
(4/30,
13%),
Parkinson
(3/30,
10%),
lower
back
pain
10%).
results
mixed
when
assessing
primary
outcome,
50%
(15/30)
finding
positive
demonstrating
nil
effect.
There
effect
3D
virtual
reality
systems
7%
(2/30)
evaluated
distinct
syndromes.
Mixed
observed
influencing
exercise
capacity;
weight;
biomarkers
disease,
such
hemoglobin
A1c,
diabetes.
In
total,
155
studied.
Most
(139/155,
89.7%)
addressed
component.
This
(11/155,
7.5%),
quality
life
(7/155,
4.8%),
physical
function
(5/155,
3.4%).
Approximately
7.7%
(12/155)
measures
represented
experience
component,
1.3%
(2/155)
addressing
cost.Given
popularity
capability,
may
play
integral
role
management.
However,
further
research
required
generate
strong
evidence
base
safe
effective
implementation.PROSPERO
International
Prospective
Register
CRD42021244562;
https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=244562.
JAMA Network Open,
Год журнала:
2023,
Номер
6(6), С. e2316634 - e2316634
Опубликована: Июнь 7, 2023
Importance
Wearable
devices
may
be
able
to
improve
cardiovascular
health,
but
the
current
adoption
of
these
could
skewed
in
ways
that
exacerbate
disparities.
Objective
To
assess
sociodemographic
patterns
use
wearable
among
adults
with
or
at
risk
for
disease
(CVD)
US
population
2019
2020.
Design,
Setting,
and
Participants
This
population-based
cross-sectional
study
included
a
nationally
representative
sample
from
Health
Information
National
Trends
Survey
(HINTS).
Data
were
analyzed
June
1
November
15,
2022.
Exposures
Self-reported
CVD
(history
heart
attack,
angina,
congestive
failure)
factors
(≥1
factor
hypertension,
diabetes,
obesity,
cigarette
smoking).
Main
Outcomes
Measures
access
devices,
frequency
use,
willingness
share
health
data
clinicians
(referred
as
care
providers
survey).
Results
Of
overall
9303
HINTS
participants
representing
247.3
million
(mean
[SD]
age,
48.8
[17.9]
years;
51%
[95%
CI,
49%-53%]
women),
933
(10.0%)
20.3
had
62.2
[17.0]
43%
37%-49%]
5185
(55.7%)
134.9
51.4
[16.9]
women).
In
weighted
assessments,
an
estimated
3.6
(18%
14%-23%])
34.5
(26%
24%-28%])
used
compared
29%
(95%
27%-30%)
adult
population.
After
accounting
differences
demographic
characteristics,
profile,
socioeconomic
features,
older
age
(odds
ratio
[OR],
0.35
0.26-0.48]),
lower
educational
attainment
(OR,
0.24-0.52]),
household
income
0.42
0.29-0.60])
independently
associated
CVD.
Among
device
users,
smaller
proportion
reported
using
every
day
(38%
26%-50%])
(49%
45%-53%])
at-risk
(48%
43%-53%])
populations.
83%
70%-92%)
81%
76%-85%)
favored
sharing
their
care.
Conclusions
Relevance
individuals
CVD,
fewer
than
4
only
half
those
reporting
consistent
daily
use.
As
emerge
tools
can
disparities
unless
there
are
strategies
ensure
equitable
adoption.
Sensors,
Год журнала:
2023,
Номер
23(13), С. 5913 - 5913
Опубликована: Июнь 26, 2023
With
the
rapid
advancement
of
information
and
communication
technology
(ICT),
big
data,
artificial
intelligence
(AI),
intelligent
healthcare
systems
have
emerged,
including
integration
with
capital,
introduction
into
long-term
care
institutions,
measurement
data
for
or
exposure.
These
provide
comprehensive
home
exposure
reports
enable
involvement
rehabilitation
specialists
other
experts.
Silver
enables
realization
health
management
in
services,
workplace
care,
applications,
facilitating
disease
prevention
control,
improving
management,
reducing
isolation,
alleviating
family
burden
terms
nursing,
promoting
control.
Research
development
efforts
forward-looking
cross-domain
precision
technology,
system
construction,
testing,
are
carried
out.
This
integrated
project
consists
two
main
components.
The
Integrated
Intelligent
Long-Term
Care
Service
Management
System
focuses
on
building
a
personalized
service
elderly,
encompassing
health,
nutrition,
diet,
education
aspects.
Wearable
Internet
Things
primarily
supports
portable
physiological
signal
detection
devices
electronic
fences.
Applied Sciences,
Год журнала:
2023,
Номер
13(3), С. 1394 - 1394
Опубликована: Янв. 20, 2023
Technology
has
played
a
vital
part
in
improving
quality
of
life,
especially
healthcare.
Artificial
intelligence
(AI)
and
the
Internet
Things
(IoT)
are
extensively
employed
to
link
accessible
medical
resources
deliver
dependable
effective
intelligent
Body
wearable
devices
have
garnered
attention
as
powerful
for
healthcare
applications,
leading
various
commercially
available
multiple
purposes,
including
individual
healthcare,
activity
alerts,
fitness.
The
paper
aims
cover
all
advancements
made
Medical
(IoMT)
systems,
which
been
scrutinized
from
perceptions
their
efficacy
detecting,
preventing,
monitoring
diseases
latest
issues
also
included,
such
COVID-19
monkeypox.
This
thoroughly
discusses
directions
proposed
by
researchers
improve
through
artificial
intelligence.
approaches
adopted
overall
accuracy,
efficiency,
security
system
discussed
detail.
highlights
constraints
opportunities
developing
AI
enabled
IoT-based
systems.
Abstract
Electronic
textiles
(e‐textiles)
have
emerged
as
a
revolutionary
solution
for
personalized
healthcare,
enabling
the
continuous
collection
and
communication
of
diverse
physiological
parameters
when
seamlessly
integrated
with
human
body.
Among
various
methods
employed
to
create
wearable
e‐textiles,
printing
offers
unparalleled
flexibility
comfort,
integrating
wearables
into
garments.
This
has
spurred
growing
research
interest
in
printed
due
their
vast
design
versatility,
material
options,
fabrication
techniques,
wide‐ranging
applications.
Here,
comprehensive
overview
crucial
considerations
fabricating
e‐textiles
is
provided,
encompassing
selection
conductive
materials
substrates,
well
essential
pre‐
post‐treatments
involved.
Furthermore,
techniques
specific
requirements
are
discussed,
highlighting
advantages
limitations
each
method.
Additionally,
multitude
applications
made
possible
by
explored,
such
integration
sensors,
supercapacitors,
heated
Finally,
forward‐looking
perspective
discussing
future
prospects
emerging
trends
realm
e‐textiles.
As
advancements
science,
technologies,
innovation
continue
unfold,
transformative
potential
healthcare
beyond
poised
revolutionize
way
technology
interacts
benefits.
Sensors,
Год журнала:
2023,
Номер
23(10), С. 4805 - 4805
Опубликована: Май 16, 2023
Worldwide,
population
aging
and
unhealthy
lifestyles
have
increased
the
incidence
of
high-risk
health
conditions
such
as
cardiovascular
diseases,
sleep
apnea,
other
conditions.
Recently,
to
facilitate
early
identification
diagnosis,
efforts
been
made
in
research
development
new
wearable
devices
make
them
smaller,
more
comfortable,
accurate,
increasingly
compatible
with
artificial
intelligence
technologies.
These
can
pave
way
longer
continuous
monitoring
different
biosignals,
including
real-time
detection
thus
providing
timely
accurate
predictions
events
that
drastically
improve
healthcare
management
patients.
Most
recent
reviews
focus
on
a
specific
category
disease,
use
12-lead
electrocardiograms,
or
technology.
However,
we
present
advances
electrocardiogram
signals
acquired
from
publicly
available
databases
analysis
methods
detect
predict
diseases.
As
expected,
most
focuses
heart
emerging
areas,
mental
stress.
From
methodological
point
view,
although
traditional
statistical
machine
learning
are
still
widely
used,
observe
an
increasing
advanced
deep
methods,
specifically
architectures
handle
complexity
biosignal
data.
typically
include
convolutional
recurrent
neural
networks.
Moreover,
when
proposing
prevalent
choice
is
rather
than
collecting
npj Digital Medicine,
Год журнала:
2024,
Номер
7(1)
Опубликована: Фев. 27, 2024
Abstract
The
annual
cost
of
hospital
care
services
in
the
US
has
risen
to
over
$1
trillion
despite
relatively
worse
health
outcomes
compared
similar
nations.
These
trends
accentuate
a
growing
need
for
innovative
delivery
models
that
reduce
costs
and
improve
outcomes.
HaH—a
program
provides
patients
acute-level
at
home—has
made
significant
progress
past
two
decades.
Technological
advancements
remote
patient
monitoring,
wearable
sensors,
information
technology
infrastructure,
multimodal
data
processing
have
contributed
its
rise
across
hospitals.
More
recently,
COVID-19
pandemic
brought
HaH
into
mainstream,
especially
US,
with
reimbursement
waivers
model
financially
acceptable
hospitals
payors.
However,
continues
face
serious
challenges
gain
widespread
adoption.
In
this
review,
we
evaluate
peer-reviewed
evidence
discuss
promises,
challenges,
what
it
would
take
tap
future
potential
HaH.